Assessing the difficulty and time cost of de-identification in clinical narratives

Methods of Information in Medicine

Volumn 45, Issue 3, 2006, Pages 246-252

  Dorr, David A ^a   Phillips, W F ^b   Phansalkar, S ^c,d   Sims, S A ^c,d   Hurdle, J F ^c,d  

^a OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

^b University of Utah   (United States)

^c UNIVERSITY OF UTAH SCHOOL OF MEDICINE   (United States)

^d VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

Computerized medical records systems; De identification; Health Insurance Portability and Accountability Act; Medical informatics computing; natural language processing

Indexed keywords

ALGORITHM; CLINICAL ASSESSMENT; CLINICAL TRIAL; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; COST BENEFIT ANALYSIS; DATA BASE; ELECTRONIC MEDICAL RECORD; GOLD STANDARD; HEALTH INSURANCE; HUMAN; MEDICAL INFORMATION; MEDICAL RESEARCH; METHODOLOGY; NARRATIVE; OUTCOME ASSESSMENT; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL; REVIEW; SENSITIVITY ANALYSIS; TRAINING; UNITED STATES; ARTICLE; CONFIDENTIALITY; COST; MEDICAL RECORD; NATURAL LANGUAGE PROCESSING; VERBAL COMMUNICATION;

CONFIDENTIALITY; COSTS AND COST ANALYSIS; HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT; HUMANS; MEDICAL RECORD LINKAGE; NARRATION; NATURAL LANGUAGE PROCESSING; UNITED STATES; UTAH;

EID: 33745562886     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.1055/s-0038-1634080     Document Type: Review

References (23)

1. Chute CG, et al. A framework for comprehensive health terminology systems in the United States: development guidelines, criteria for selection, and public policy implications. ANSI Healthcare Informatics Standards Board Vocabulary Working Group and the Computer-Based Patient Records Institute Working Group on Codes and Structures. J Am Med Inform Assoc 1998; 5 (6): 503-10.
2. NIH Draft Statement on Sharing Research Data. Bethesda, MD: NIH; 2002 [accessed April 24, 2005]. Available from: http://grantsl.nih.gov/grants/guide/ notice-files/NOT-OD-02-035.html.
3. Berman JJ. Confidentiality issues for medical data miners. Artif Intell Med 2002; 26 (1-2): 25-36.
4. Initiative on Privacy Standardisation in Europe (IPSE): Final Report. Brussels, Belgium: CEN/ISSS; 2002 [Accessed Aug 25, 2005]. Available at: http://www.cenorm.be/cenorm/businessdomains/businessdomains/isss/activity/ ipsefinalreport.pdf
5. Fielstein E, et al. Algorithmic De-identification of VA Medical Exam Text for HIPAA Privacy Compliance: Preliminary Findings. Medinfo 2004; 11 (Pt 1): 1590.
6. Thomas SM, et al. A successful technique for removing names in pathology reports using an augmented search and replace method. Proc AMIA Symp 2002; pp 777-81.
7. Ruch P, et al. Medical document anonymization with a semantic lexicon. Proc AMIA Symp 2000; pp 729-33.
8. Taira RK, et al. Identification of patient name references within medical documents using semantic selectional restrictions. Proc AMIA Symp 2002; pp 757-61.
9. Security and Privacy Workgroup (WEDI). De-identification white paper (version 3.1) (monograph on the internet). Reston, VA: Workgroup for Electronic Data Interchange; 2001 /cited Aug 25, 2005): 1-12. Available from: http://privacy.cs. cmu.edu/dataprivacy/HIPAA/SNIPdeidv31.pdf
10. Baker S, et al. Anonymization, data-matching and privacy: a case study. Final report. Washington. DC: Steptoe & Johnson, LLP; 2003.
11. Sweeney L. Replacing personally-identifying information in medical records, the Scrub system. Proc AMIA Annu Fall Symp 1996; pp 333-7.
12. Quantin C, et al. Automatic record hash coding and linkage for epidemiological follow-up data confidentiality. Methods Inf Med 1998; 37 (3): 271-7.
13. Quantin C, et al. Decision analysis for the assessment of a record linkage procedure: application to a perinatal network. Methods Inf Med 2005; 44 (1): 72-9.
14. Berman JJ. Concept-match medical data scrubbing. How pathology text can be used in research. Arch Pathol Lab Med 2003; 127 (6): 680-6.
15. Ohno-Machado L, et al. Protecting patient privacy by quantifiable control of disclosures in disseminated databases. Int J Med Inform 2004; 73 (7-8): 599-606.
16. Berman JJ. Zero-check: a zero-knowledge protocol for reconciling patient identities across institutions. Arch Pathol Lab Med 2004; 128 (3): 344-6.
17. Sweeney L. Guaranteeing anonymity when sharing medical data, the Datafly System. Proc AMIA Annu Fall Symp 1997; pp 51-5.
18. Gupta D, et al. Evaluation of a deidentification (De-Id) software engine to share pathology reports and clinical documents for research. Am J Clin Pathol 2004; 121(2): 176-86.
19. Chinchor N. Overview of MUC-7/MET-2 [monograph on the internet]. Science Applications International Corporation; 1998 [accessed Aug 25, 2005]. Available at: http://www.itl.nist.gov/iaui/894.02/related_projects/muc/proceedings/ muc_7_proceedings/overview.html
20. Hirschman L, et al. Rutabaga by any other name: extracting biological names. J Biomed Inform 2002; 35 (4): 247-59.
21. Nebeker J, et al. High rates of adverse drug events in a highly computerized hospital. Arch Intern Med 2005; 165 (10): 1111-6.
22. Bruce R, Wiebe J. Recognizing Subjectivity: A case study of manual tagging. Natural Language Engineering 1999; 5 (2): 1-16.
23. Streiner D, Norman G. Health Measurement Scales: A Practical Guide to Their Development and Use. 2nd ed. New York: Oxford University Press; 1995.